Intelligent service robots are becoming the cusp of the industry. Starting from cleaning robots , family companion robots and food delivery robots have entered the public eye. When discussing whether such robots can solve practical problems, autonomous positioning navigation technology as the first step of robot intelligence is constantly attracting attention in the industry. At the same time, as an important breakthrough in autonomous positioning navigation technology, SLAM technology has also become the focus of attention. As shown in the figure, the robot autonomous positioning navigation technology includes positioning, map creation and path planning (motion control), while SLAM itself is only two things to complete the robot positioning and map construction, the two are not completely equivalent. So, how is SLAM technology implemented? What are the difficulties? How does the robot implement path planning and automatic navigation? What kind of sweeping robot is smart? These questions, Xiaobian will answer you one by one, leading everyone to understand the secret of robotic autonomous movement. Today, let's start with SLAM. SLAM is an abbreviation for Simultaneous Localization And Mapping, first proposed by Hugh Durrant-Whyte and John J. Leonard. In fact, SLAM is more like a concept than an algorithm. It itself contains many steps, each of which can be implemented using different algorithms. SLAM is mainly used to solve the problem of real-time positioning and map construction when mobile robots operate in an unknown environment. When you are in a different place, how can you find exactly where you want to go? How do you find a way home when you get lost outdoors? Yes, we have navigation software and outdoor maps.
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